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Direct simulation of a stochastically driven multi-step birth-death process

Gorin, Gennady and Pachter, Lior (2021) Direct simulation of a stochastically driven multi-step birth-death process. . (Unpublished)

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The description of transcription as a stochastic process provides a framework for the analysis of intrinsic and extrinsic noise in cells. To better understand the behaviors and possible extensions of existing models, we design an exact stochastic simulation algorithm for a multimolecular transcriptional system with an Ornstein-Uhlenbeck birth rate that is implemented via a special function-based time-stepping algorithm. We demonstrate that its joint copy-number distributions reduce to analytically well-studied cases in several limiting regimes, and suggest avenues for generalizations.

Item Type:Report or Paper (Discussion Paper)
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URLURL TypeDescription Paper ItemData
Gorin, Gennady0000-0001-6097-2029
Pachter, Lior0000-0002-9164-6231
Additional Information:The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. Version 1 - January 21, 2021; Version 2 - March 3, 2021. The DNA, pre-mRNA, and mature mRNA illustrations used in Figure 2, reproduced from [34], are derivatives of the DNA Twemoji by Twitter, Inc., used under CC-BY 4.0. G.G. and L.P. were partially funded by NIH U19MH114830. Code availability: MATLAB code that can be used to reproduce Figures 4-S3, including the simulation and plotting routines, is available at The authors have declared no competing interest.
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Record Number:CaltechAUTHORS:20210122-125501964
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Official Citation:Direct simulation of a stochastically driven multi-step birth-death process. Gennady Gorin, Lior Pachter. bioRxiv 2021.01.20.427480; doi:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107661
Deposited By: Tony Diaz
Deposited On:22 Jan 2021 21:19
Last Modified:16 Nov 2021 19:05

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